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Artists portray human faces with the Fourier statistics of complex natural scenes

Institute of Anatomy I, School of Medicine, Friedrich Schiller University, Germany.
Network Computation in Neural Systems (Impact Factor: 0.5). 10/2007; 18(3):235-48. DOI: 10.1080/09548980701574496
Source: PubMed

ABSTRACT When artists portray human faces, they generally endow their portraits with properties that render the faces esthetically more pleasing. To obtain insight into the changes introduced by artists, we compared Fourier power spectra in photographs of faces and in portraits by artists. Our analysis was restricted to a large set of monochrome or lightly colored portraits from various Western cultures and revealed a paradoxical result. Although face photographs are not scale-invariant, artists draw human faces with statistical properties that deviate from the face photographs and approximate the scale-invariant, fractal-like properties of complex natural scenes. This result cannot be explained by systematic differences in the complexity of patterns surrounding the faces or by reproduction artifacts. In particular, a moderate change in gamma gradation has little influence on the results. Moreover, the scale-invariant rendering of faces in artists' portraits was found to be independent of cultural variables, such as century of origin or artistic techniques. We suggest that artists have implicit knowledge of image statistics and prefer natural scene statistics (or some other rules associated with them) in their creations. Fractal-like statistics have been demonstrated previously in other forms of visual art and may be a general attribute of esthetic visual stimuli.

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    ABSTRACT: In the last decades many neuroscientists have started to investigate the perception of nature and art by the human visual system. Natural scenes lead to an esthetically pleasing perception, therefore scientists have begun to research the reasons to understand the processing principles of the human visual system. @InProceedings{koch_et_al:DSP:2009:1868, author = {Michael Koch and Joachim Denzler and Christoph Redies}, title = {Universal Image Statistics as a Basis for Esthetic Perception}, booktitle = {Computer Vision in Camera Networks for Analyzing Complex Dynamic Natural Scenes}, year = {2009}, editor = {Joachim Denzler and Michael Koch}, publisher = {Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany}, address = {Dagstuhl, Germany}, URL = {http://drops.dagstuhl.de/opus/volltexte/2009/1868}, annote = {Keywords: Esthetic, Aesthetic, PCA, Power Spectrum, Principal Component Analysis}, }
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